GHSA-gj55-2xf9-67rq
HIGHHTML injection in JupyterLite leading to DOM Clobbering
Blast Radius
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Description
Impact
The vulnerability depends on user interaction by opening a malicious notebook with Markdown cells, or Markdown file using JupyterLab preview feature.
A malicious user can access any data accessible from JupyterLite and perform arbitrary actions in JupyterLite environment.
Patches
JupyterLite 0.4.1 was patched.
Workarounds
There is no workaround for the underlying DOM Clobbering susceptibility. However, select plugins can be disabled on deployments which cannot update in a timely fashion to minimise the risk. These are:
@jupyterlab/mathjax-extension:plugin- users will loose ability to preview mathematical equations@jupyterlab/markdownviewer-extension:plugin- users will loose ability to open Markdown previews@jupyterlab/mathjax2-extension:plugin(if installed with optionaljupyterlab-mathjax2package) - an older version of the mathjax plugin for JupyterLab 4.x
To disable these extensions populate the disabledExtensions key in jupyter-config-data stanza of jupyter-lite.json as documented on https://jupyterlite.readthedocs.io/en/stable/howto/configure/config_files.html#jupyter-lite-json
{
"jupyter-lite-schema-version": 0,
"jupyter-config-data": {
"appName": "My JupyterLite App",
"disabledExtensions": [
"@jupyterlab/markdownviewer-extension:plugin",
"@jupyterlab/mathjax-extension:plugin",
"@jupyterlab/mathjax2-extension:plugin"
]
}
}
To confirm that the plugins were disabled manual inspection of the built page is required.
References
Upstream advisory: https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-9q39-rmj3-p4r2
Notes
This change has a potential to break rendering of some markdown. There is a setting in Sanitizer which allows to revert to the previous sanitizer settings (allowNamedProperties).
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | jupyterlite-core | all versions | 0.4.1 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterlite-core. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update jupyterlite-core to 0.4.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-gj55-2xf9-67rq is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-gj55-2xf9-67rq is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-gj55-2xf9-67rq. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-gj55-2xf9-67rq in your dependencies?
O3 detects GHSA-gj55-2xf9-67rq across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.